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--- |
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language: |
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- sk |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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metrics: |
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- wer |
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base_model: mikr/whisper-small-cs-cv11 |
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model-index: |
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- name: Whisper Small Slovak test on Czech |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: mozilla-foundation/common_voice_11_0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: sk |
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split: test |
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args: sk |
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metrics: |
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- type: wer |
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value: 35.43550690147549 |
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name: Wer |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper Small Slovak test on Czech |
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This model is a fine-tuned version of [mikr/whisper-small-cs-cv11](https://huggingface.co/mikr/whisper-small-cs-cv11) on the mozilla-foundation/common_voice_11_0 sk dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7223 |
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- Wer: 35.4355 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 5000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 0.001 | 21.0 | 1000 | 0.6507 | 37.3275 | |
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| 0.0003 | 42.01 | 2000 | 0.6954 | 36.1138 | |
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| 0.0002 | 63.01 | 3000 | 0.7223 | 35.4355 | |
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| 0.0001 | 85.0 | 4000 | 0.7388 | 35.5902 | |
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| 0.0001 | 106.0 | 5000 | 0.7465 | 35.6735 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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